Classifier systems and genetic algorithms
Artificial Intelligence
Intelligence without representation
Artificial Intelligence
An Behavior-based Robotics
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Flesh and Machines: How Robots Will Change Us
Flesh and Machines: How Robots Will Change Us
A Distributed Model for Mobile Robot Environment-Learning and Navigation
A Distributed Model for Mobile Robot Environment-Learning and Navigation
Interaction and Intelligent Behavior
Interaction and Intelligent Behavior
Autonomous Robots: From Biological Inspiration to Implementation and Control (Intelligent Robotics and Autonomous Agents)
Simple target seek based on behavior
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
WSEAS Transactions on Systems and Control
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This work presents a solution to a mobile robot autonomous navigation utilizing minimum representation of the environment. It is done under simulation of a differential wheels robot inside a 2D environment with a layout very close to a real situation for laboratories, offices and classrooms. The solution takes into consideration local and long run navigation and utilizes only behavior-based architecture. A first approach utilizes only reactive behaviors solving very well local navigation. It also gives a partial solution to long run navigation in a simple environment, with only two rooms, doing that without path definition. A complete solution for an environment with many rooms is developed adding to the previous approach more behaviors that will take care of path definition and control. A linear graph, having the passages as landmarks, structures the environment representation and is the basis for the algorithm of path definition that gives an efficient solution. The approach used does not show a central planner and controller as in traditional deliberative architectures; planning and control arises from the independent parallel functioning of all the behaviors.